Group Testing Research Articles

The Performance of Pooled 3 Anatomic Site Testing for Chlamydia trachomatis and Neisseria gonorrhoeae Among Men Who Have Sex With Men and Transgender Women.

Although molecular testing for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) is highly sensitive, the cost can be prohibitive. Those high costs are amplified when the recommended screening approach is used, which requires separate testing of specimens from 3 anatomic sites (rectal, pharyngeal and urogenital). Although individual molecular testing is standard of care, pooled testing may offer a cost-saving alternative. Using the Xpert® CT/NG assay (Cepheid, Sunnyvale, CA) we tested urine, rectal and pharyngeal swabs for CT and NG in a high-risk cohort of participants assigned male at birth who reported sex with other persons who were assigned male at birth. Remnant specimens (0.34 mL from each anatomic site) were combined to perform a single 'pooled' test. We calculated positive and negative percent agreement between the pooled testing results with standard of care Xpert CT/NG test results as the reference. We conducted 644 pooled tests. Of those, 598 (92.3%) gave CT and NG results. The CT-positive and -negative percent agreement were 90.1% (95% confidence interval [CI], 80.7-95.9%) and 99.2% (98.1-99.8%), respectively. The NG-positive and -negative percent agreement were 96.2% (95% CI, 86.8-99.5%) and 99.8% (95% CI, 99.0-100%), respectively. Pooled testing identified 4 CT and 1 NG infections that were negative at all anatomic sites by individual testing. Three-site pooled CT and NG testing performs similarly to single anatomic site testing among tests providing a valid result. Future cost analyses should evaluate the cost effectiveness of pooled 3-site testing to determine if such a strategy improves the feasibility and accessibility of molecular sexually transmitted infection testing.

Optimal Testing under Limited Capacity

Motivated by the persistent lack of testing capacity in the COVID-19 pandemic, we study the question “who should be tested?” when capacity is limited, tests have errors, and patients differ in their prior probability of being infected. While health officials initially prioritized testing patients who were highly likely to be infected, we find that it may be better to focus on patients who are less likely to be infected, particularly when the false-negative rate is substantial. We also consider pooled testing, a method of grouping samples to conserve tests. When pooled testing is an option, it may be optimal to test two groups of individuals: those who are very likely to be infected and those who are very unlikely to be infected. Moreover, even though pooling is an option, it can still be optimal to reserve some individual tests for samples from patients for whom the outcome is most uncertain. The results apply to any situation where testing capacity is inadequate to test the number of potentially infected individuals, and they can inform both public health policy and healthcare operations management.

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources, with application to COVID-19.

Testing provides essential information for managing infectious disease outbreaks, such as the COVID‐19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease‐positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false‐negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data‐driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID‐19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID‐19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.

Can't Work From Home: Pooled Nucleic Acid Testing of Laboratory Workers During the COVID-19 Pandemic.

Together with protective measures, routine screening for severe acute respiratory syndrome coronavirus 2 infection helps provide a safe working environment. We evaluated a pooled nucleic acid testing strategy in a research laboratory. It allowed lab activity to be maintained and would save 25 920 person-hours and $1 684 800/year by increasing the margin of safety for returning to work.

A detailed mechanism for the initial hypergolic reaction in liquid hydrazine/nitrogen tetroxide mixtures based on quantum chemistry calculations

This work determined a chemical mechanism for the early stage of hypergolic ignition following contact between hydrazine (N2H4) and nitrogen tetroxide (N2O4), both in the liquid state. Such mixtures have been used in thrusters for spacecraft applications for many years, and the effective development and use of such propellants requires an understanding of their detonation-like ignition under various conditions. Liquid-phase reactions were investigated using quantum chemical calculations at the CBS-QB3//ωB97X-D/SMD level of theory, and the results showed that the energy barrier to the reaction N2H4 + N2O4 → NH2NHNO2 + HNO2 was much lower than values predicted for the same reaction in the gas phase. Based on these results, a detailed kinetic model for the liquid-phase reaction was constructed and employed to predict the temperature increase obtained from N2H4/N2O4 propellants under pre-mixed and adiabatic conditions. The time to reach the N2H4 boiling point of 114 °C was estimated at approximately 0.06 μs, which explains the rapid formation of a vapor phase in previous droplet pool tests. Analyses of the rate of production and the temperature sensitivity established that the N2H4 + N2O4 → NH2NHNO2 + HNO2 step plays the most important role in triggering a series of subsequent reactions, and thus determines the rate of temperature rise.

Comparing two sample pooling strategies for SARS-CoV-2 RNA detection for efficient screening of COVID-19.

The emerging pandemic of coronavirus disease 2019 (COVID-19) has affected over 200 countries and resulted in a shortage of diagnostic resources globally. Rapid diagnosis of COVID-19 is vital to control the spreading of the disease, which, however, is challenged by limited detection capacity and low detection efficiency in many parts of the world. The pooling test may offer an economical and effective approach to increase the virus testing capacity of medical laboratories without requiring more laboratory resources such as laboratory workers, testing reagents, and equipment. In this study, the sample pools of 6 and 10 were detected by a real-time reverse transcription-polymerase chain reaction assay targeting ORF1ab and N genes of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Each pool consisted of five or nine negative SARS-CoV-2 samples and one positive counterpart with varying viral loads. Two different strategies of sample pooling were investigated and the results were compared comprehensively. One approach was to pool the viral transport medium of the samples in the laboratory, and the other was to pool swab samples during the collection process. For swab pooling strategy, qualitative results of SARS-CoV-2 RNA, specific tests of ORF1ab and N genes, remained stable over the different pool sizes. Together, this study demonstrates that the swab pooling strategy may serve as an effective and economical approach for screening SARS-CoV-2 infections in large populations, especially in countries and regions where medical resources are limited during the pandemic and may thus be potential for clinical laboratory applications.

Design and Implementation of an Adaptive Pooling Workflow for SARS-CoV-2 Testing in an NHS Diagnostic Laboratory

Background: Diagnostic laboratories are currently required to provide routine testing of asymptomatic staff and patients as a part of their clinical screening for SARS-CoV-2 infection. However, these cohorts display very different disease prevalence from symptomatic individuals and testing capacity for asymptomatic screening is often limited. Group testing is frequently proposed as a possible solution to address this; however, proposals neglect the technical and operational feasibility of implementation in a front-line diagnostic laboratory. Methods: Between October and December 2020, as a 7-week proof of concept, we took into account scientific, technical and operational feasibility to design and implement an adaptive pooling strategy in an NHS diagnostic laboratory in London (UK). We assessed the impact of pooling on analytical sensitivity and modelled the impact of prevalence on pooling strategy. We then considered the operational constraints to model the potential gains in capacity and the requirements for additional staff and infrastructure. Finally, we developed a LIMS-agnostic laboratory automation workflow and software solution and tested the technical feasibility of our adaptive pooling workflow. Findings: First, we determined the analytical sensitivity of the implemented SARS-CoV-2 assay to be 250 copies/mL. We then determined that, in a setting with limited analyser capacity, the testing capacity could be increased by two- fold with pooling, however, in a setting with limited reagents, this could rise to a five-fold increase. These capacity increases could be realized with modest additional resource and staffing requirements whilst utilizing up to 76% fewer plastic consumables and 90% fewer reagents. Finally, we successfully implemented a plate-based pooling workflow and tested 920 patient samples using the reagents that would usually be required to process just 222 samples. Interpretation: Adaptive pooled testing is a scientifically, technically and operationally feasible solution to increase testing capacity in frontline NHS diagnostic laboratories. Funding: NHS England Declaration of Interests: ZH and LAP are employed by Riffyn, Inc. MAC and PSF are consultants for Analytik Jena. All other authors declare no competing interests.

Mathematical formation and analysis of COVID-19 pool tests strategies

Abstract Objectives The excessive spread of the pandemic COVID-19 around the globe has put mankind at risk. The medical infrastructure and resources are frazzled, even for the world's top economies, due to the large COVID-19 infection. To cope up with this situation, countries are exploring the pool test strategies. In this paper, a detailed analysis has been done to explore the efficient pooling strategies. Given a population and the known fact that the percentage of people infected by the virus, the minimum number of tests to identify COVID-19 positive cases from the entire population are found. In this paper, the problem is formulated with an objective to find a minimum number of tests in the worst case where exactly one positive sample is there in a pool which can happen considering the fact that the groups are formed by choosing samples randomly. Therefore, the thrust stress is on minimizing the total number of tests by finding varying pool sizes at different levels (not necessarily same size at all levels), although levels can also be controlled. Methods Initially the problem is formulated as an optimization problem and there is no constraint on the number of levels upto which pooling can be done. Finding an analytical solution of the problem was challenging and thus the approximate solution was obtained and analyzed. Further, it is observed that many times it is pertinent to put a constraint on the number of levels upto which pooling can be done and thus optimizing with such a constraint is also done using genetic algorithm. Results An empirical evaluation on both realistic and synthetic examples is done to show the efficiency of the procedures and for lower values of percentage infection, the total number of tests are very much less than the population size. Further, the findings of this study show that the general COVID-19 pool test gives the better solution for a small infection while as the value of infection becomes significant the single COVID-19 pool test gives better results. Conclusions This paper illustrates the formation and analysis of polling strategies, which can be opted for the better utilization of the resources. Two different pooling strategies are proposed and these strategies yield accurate insight considering the worst case scenario. The analysis finds that the proposed bounds can be efficiently exploited to ascertain the pool testing in view of the COVID-19 infection rate.

Infection Testing at Scale: An Examination of Pooled Testing Diagnostics

Executive Summary In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals without adequate testing kits. We propose a testing protocol to accelerate infection diagnostics by combining multiple samples, and in case of positive results, re-test individual samples. The key insight is that a negative result in the first stage implies negative infection for all individuals. Thus, a single test could rule out infection in multiple individuals. Using simulations, we show that this protocol reduces the required number of testing kits, especially when the infection rate is low, alleviating a key bottleneck for public health authorities in times of pandemics and epidemics such as COVID-19. Our proposed protocol is expected to be more effective when the infection rate is low, which suggests that it is better suited for early stage and large-scale, population-wide testing. However, the managerial trade-off is that the protocol has costs in additional time for returning test results and an increased number of false negatives. We discuss applications of pooled testing in understanding population-wide testing to understand infection prevalence, to diagnose infections in high-risk groups of individuals, and to identify disease cold spots.

Pooled-sample testing for detection of Mycoplasma hyopneumoniae during late experimental infection as a diagnostic tool for a herd eradication program

Early and accurate detection of Mycoplasma hyopneumoniae infection in live pigs is a critical component to measure the success of disease eradication strategies. However, the imperfect sensitivity of in vivo diagnostic tools, change in sensitivity over the course of infection, and expected low prevalence level at the end of an eradication program create a challenging diagnostic scenario. Here, the individual and pool sensitivities for detection of M. hyopneumoniae during the chronic phase of infection was determined using deep tracheal catheter samples, the in vivo sample type with the highest reported diagnostic sensitivity. Fifty samples from known infected pigs collected at 113 days post-M. hyopneumoniae intra-tracheal inoculation, were diluted in known negative samples to form pools of 1:3 and 1:5. Samples were tested for M. hyopneumoniae by a species-specific PCR. Ninety-eight percent (49/50) of individual samples, 84 % (42/50) of pools of 1:3, and 82 % (41/50) of 1:5 were detected positive for M. hyopneumoniae. To apply the sensitivity estimates for detection of M. hyopneumoniae in a low prevalence scenario, sample sizes with associated sample collection costs were calculated for individual and pooled testing using algorithms within the program EpiTools One-Stage Freedom Analyses. Assumptions included a ≥95 % population sensitivity, infinite population size, prevalence levels of ≥0.5 %, ≥1 %, ≥2 %, ≥3 %, ≥4 %, or ≥5 %, 100 % specificity, along with the mean and lower confidence limit of the individual or pool sensitivity for each pool size, when appropriate. For instance, following completion of a herd eradication program, if a low risk approach is targeted, sample size estimates for ≥2 % prevalence using the lower limit of the diagnostic or pool sensitivity 95 %CI may be followed. If samples were to be tested individually, 167 individuals would be sampled at a cost of 6,012 USD. If pooled by 3, 213 would be sampled (testing cost 3,266 USD), and for pools of 5, 220 individuals would be sampled (testing cost 2,464 USD). Population sensitivity was also calculated for a range of testing scenarios. Our study indicated that pooling samples by 3 or 5 was a cost-effective method for M. hyopneumoniae detection in low prevalence scenarios. Cost-effective detection was evidenced despite the increased sample collection costs associated with large sample sizes in order to offset decreased testing sensitivity attributable to pooling. The post-eradication sample collection scheme, combined with pooling, suggested lower cost options than individual sampling for testing to be applied at the end of an eradication program, without significantly compromising the likelihood of detection.

Intricacies in characterizing positivity in pooled sample testing for SARS-CoV-2.

The unprecedented demand for testing for the ongoing coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 has led to an acute shortage and limited availability of test reagents for which pooling of samples has been recommended in areas with low prevalence. Considering the possibility of dilution factor in pool testing, an attempt was made to find out possibility of any true positive samples in pools with late amplification. The study was conducted on samples received from various collection centers in different districts of Odisha as well as from patients attending the screening clinic or admitted in COVID ward of the hospital. Nasal/nasopharyngeal/throat swabs received in viral transport media in cold chain were subjected to Real-time polymerase chain reaction (RT-PCR) testing in a Biosafety Laboratory level-2 by including uniform volume of four units (samples) per pool. All confirmed and probable positive pools in screening assay were de-convoluted and individual samples tested for confirmatory assay. Inclusion of an additional criteria of probable positive pool (Ct value >35 with non-sigmoid amplification curve or showing a line of amplification towards the end of the cycle) yielded 39 (15.5%) more true positive samples out of a total of 251 positive samples that would otherwise have been missed if only the classical criteria of positive (Ct within 35 with proper sigmoid curve) had been considered. The study highlights the importance of considering any indication of late amplification in the RT-PCR test to label a pool as positive to avoid missing any true positive sample in the pool.

Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings.

Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combined a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence and to ratify sensitivity losses against the time course of individual infections. We show that prevalence can be accurately estimated across a broad range, from 0.02 to 20%, using only a few dozen pooled tests and using up to 400 times fewer tests than would be needed for individual identification. We then exhaustively evaluated the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many true positives as individual testing with a given budget. Crucially, we confirmed that our theoretical results can be translated into practice using pooled human nasopharyngeal specimens by accurately estimating a 1% prevalence among 2304 samples using only 48 tests and through pooled sample identification in a panel of 960 samples. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.

Saliva Pooling Strategy for the Large-Scale Detection of SARS-CoV-2, Through Working-Groups Testing of Asymptomatic Subjects for Potential Applications in Different Workplaces.

Objective:To perform an improved large-scale SARS-CoV-2 detection on pooled tests of asymptomatic workers.Methods:qRT-PCR validation of the SARS-CoV-2 detection in salivae samples and saliva pools and working-group saliva pooling and testing for SARS-CoV-2.Results:We found a high Cycle threshold correlation (r = 0.9099) between swabs and saliva samples. Then, through the pooling strategy, we detected that 18/360 (5%) of individual saliva samples were SARS-CoV-2 positive. Saliva-pooling efficiency (360 of test sample/30 individual PCR) was higher (5.45) than the reported for swabbing group-testing and we spared 82% of the PCR reagents as well as sampling and personal protection equipment.Conclusion:Through this simplified and less expensive procedure, we detected in a short time asymptomatic-infected SARS-CoV-2-carriers that were isolated from their co-workers, thus, this methodology can be implemented in different workplaces to ensure consumers that employees are not infectious.

Simulation modelling to estimate the herd-sensitivity of various pool sizes to test beef herds for Johne's disease in Australia

Johne’s disease is a chronic intestinal disease affecting livestock. It leads to the shedding of Mycobacterium avium subspecies paratuberculosis (MAP) in the faeces, wasting and eventually death, with animal welfare, economic, and trade implications. The Johne’s Beef Assurance Scheme, used in Australia to determine the risk of Johne’s disease on beef properties and facilitate trade, is based on testing a subset of the herd with pooled faecal quantitative PCR. This study aimed to model the herd-sensitivity of pooled faecal testing under different Australian farming scenarios. Animals from simulated herds were randomly sampled and allocated into their respective pools. Each tested pool was provided a test outcome, with herd-sensitivity estimated as the probability of detecting a truly infected herd. The models simulated the test performance for the ‘Sample’ and ‘Check’ tests used in the assurance schemes (recommended sample sizes of 300 and 50, respectively) for a range of herd sizes, infection prevalence and MAP faecal shedding levels for the pool sizes of 5, 10, 15 and 20. Sensitivity and specificity input values of each pool size were obtained from a previous laboratory investigation. The herd-sensitivity estimate increased with herd size and infection prevalence levels, regardless of the pool size. Higher herd-sensitivity was also achieved for testing scenarios involving larger sample sizes. A pool size of 10 achieved similar herd-sensitivity to that of the current pool size for the majority of the Sample test and Check test scenarios. This was particularly evident when pool-specificity was assumed to be perfect. The overall herd-sensitivity of the Check test was very low for all infection prevalence levels and pool sizes, but it more than doubled, when the sample size increased from 50 to 100 animals (11% versus 26% for a herd size of 500 cattle with a 2% infection prevalence). The results show that the majority of beef producers participating in the assurance scheme can benefit from using a larger pool size for the pooled faecal quantitative PCR testing of their herd, in comparison to the pool size currently used.

A robust pooled testing approach to expand COVID-19 screening capacity.

Limited testing capacity for COVID-19 has hampered the pandemic response. Pooling is a testing method wherein samples from specimens (e.g., swabs) from multiple subjects are combined into a pool and screened with a single test. If the pool tests positive, then new samples from the collected specimens are individually tested, while if the pool tests negative, the subjects are classified as negative for the disease. Pooling can substantially expand COVID-19 testing capacity and throughput, without requiring additional resources. We develop a mathematical model to determine the best pool size for different risk groups, based on each group’s estimated COVID-19 prevalence. Our approach takes into consideration the sensitivity and specificity of the test, and a dynamic and uncertain prevalence, and provides a robust pool size for each group. For practical relevance, we also develop a companion COVID-19 pooling design tool (through a spread sheet). To demonstrate the potential value of pooling, we study COVID-19 screening using testing data from Iceland for the period, February-28-2020 to June-14-2020, for subjects stratified into high- and low-risk groups. We implement the robust pooling strategy within a sequential framework, which updates pool sizes each week, for each risk group, based on prior week’s testing data. Robust pooling reduces the number of tests, over individual testing, by 88.5% to 90.2%, and 54.2% to 61.9%, respectively, for the low-risk and high-risk groups (based on test sensitivity values in the range [0.71, 0.98] as reported in the literature). This results in much shorter times, on average, to get the test results compared to individual testing (due to the higher testing throughput), and also allows for expanded screening to cover more individuals. Thus, robust pooling can potentially be a valuable strategy for COVID-19 screening.

Sample pooling as a strategy for community monitoring for SARS-CoV-2

Sample pooling strategy was intended to determine the optimal parameters for group testing of pooled specimens for the detection of SARS-CoV-2 and process them without significant loss of test usability. Standard molecular diagnostic laboratory equipment, and commercially available centrifugal filters, RNA isolation kits and SARS Cov2 PCR tests were used. The basic idea was to combine and concentrate several samples to the maximal volume, which can be extracted with the single extraction column. Out of 16 tested pools, 12 were positive with cycle threshold (Ct) values within 0.5 and 3.01 Ct of the original individual specimens. The analysis of 112 specimens determined that 12 pools were positive, followed by identification of 6 positive individual specimens among the 112 tested. This testing was accomplished with the use of 16 extractions/PCR tests, resulting in saving of 96 reactions but adding the 40 centrifugal filters. The present study demonstrated that pool testing could detect even up to a single positive sample with Ct value as high as 34. According to the standard protocols, reagents and equipment, this pooling method can be applied easily in current clinical testing laboratories.

Swab pooling: A new method for large-scale RT-qPCR screening of SARS-CoV-2 avoiding sample dilution.

To minimize sample dilution effect on SARS-CoV-2 pool testing, we assessed analytical and diagnostic performance of a new methodology, namely swab pooling. In this method, swabs are pooled at the time of collection, as opposed to pooling of equal volumes from individually collected samples. Paired analysis of pooled and individual samples from 613 patients revealed 94 positive individuals. Having individual testing as reference, no false-positives or false-negatives were observed for swab pooling. In additional 18,922 patients screened with swab pooling (1,344 pools), mean Cq differences between individual and pool samples ranged from 0.1 (Cr.I. -0.98 to 1.17) to 2.09 (Cr.I. 1.24 to 2.94). Overall, 19,535 asymptomatic patients were screened using 4,400 RT-qPCR assays. This corresponds to an increase of 4.4 times in laboratory capacity and a reduction of 77% in required tests. Therefore, swab pooling represents a major alternative for reliable and large-scale screening of SARS-CoV-2 in low prevalence populations.

Pooled testing conserves SARS-CoV-2 laboratory resources and improves test turn-around time: experience on the Kenyan Coast.

Background. International recommendations for the control of the coronavirus disease 2019 (COVID-19) pandemic emphasize the central role of laboratory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent, at scale. The availability of testing reagents, laboratory equipment and qualified staff are important bottlenecks to achieving this. Elsewhere, pooled testing (i.e. combining multiple samples in the same reaction) has been suggested to increase testing capacities in the pandemic period. Methods. We discuss our experience with SARS-CoV-2 pooled testing using real-time reverse transcription polymerase chain reaction (RT-PCR) on the Kenyan Coast. Results. In mid-May, 2020, our RT-PCR testing capacity for SARS-CoV-2 was improved by ~100% as a result of adoption of a six-sample pooled testing strategy. This was accompanied with a concomitant saving of ~50% of SARS-CoV-2 laboratory test kits at both the RNA extraction and RT-PCR stages. However, pooled testing came with a slight decline of test sensitivity. The RT-PCR cycle threshold value (ΔCt) was ~1.59 higher for samples tested in pools compared to samples tested singly. Conclusions. Pooled testing is a useful strategy to increase SARS-CoV-2 laboratory testing capacity especially in low-income settings.

Performance of Unobserved Self-Collected Nasal Swabs for Detection of SARS-CoV-2 by RT-PCR Utilizing a Remote Specimen Collection Strategy.

BackgroundThe use of a remote specimen collection strategy employing a kit designed for unobserved self-collection for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcription polymerase chain reaction (RT-PCR) can decrease the use of personal protective equipment (PPE) and exposure risk. To assess the impact of unobserved specimen self-collection on test performance, we examined results from a SARS-CoV-2 qualitative RT-PCR test for self-collected specimens from participants in a return-to-work screening program and assessed the impact of a pooled testing strategy in this cohort.MethodsSelf-collected anterior nasal swabs from employee return-to-work programs were tested using the Quest Diagnostics Emergency Use Authorization SARS-CoV-2 RT-PCR. The cycle threshold (Ct) values for the N1 and N3 N-gene targets and a human RNase P (RP) gene control target were tabulated. For comparison, we utilized Ct values from a cohort of health care provider–collected specimens from patients with and without coronavirus disease 2019 symptoms.ResultsAmong 47 923 participants, 1.8% were positive. RP failed to amplify for 13/115 435 (0.011%) specimens. The median (interquartile range) Cts were 32.7 (25.0–35.7) for N1 and 31.3 (23.8–34.2) for N3. Median Ct values in the self-collected cohort were significantly higher than those of symptomatic but not asymptomatic patients. Based on Ct values, pooled testing with 4 specimens would have yielded inconclusive results in 67/1268 (5.2%) specimens but only a single false-negative result.ConclusionsUnobserved self-collection of nasal swabs provides adequate sampling for SARS-CoV-2 RT-PCR testing. These findings alleviate concerns of increased false negatives in this context. Specimen pooling could be used for this population, as the likelihood of false-negative results is very low when using a sensitive, dual-target methodology.

Optimal group testing

AbstractIn the group testing problem the aim is to identify a small set of k ⁓ nθ infected individuals out of a population size n, 0 < θ < 1. We avail ourselves of a test procedure capable of testing groups of individuals, with the test returning a positive result if and only if at least one individual in the group is infected. The aim is to devise a test design with as few tests as possible so that the set of infected individuals can be identified correctly with high probability. We establish an explicit sharp information-theoretic/algorithmic phase transition minf for non-adaptive group testing, where all tests are conducted in parallel. Thus with more than minf tests the infected individuals can be identified in polynomial time with high probability, while learning the set of infected individuals is information-theoretically impossible with fewer tests. In addition, we develop an optimal adaptive scheme where the tests are conducted in two stages.